What is the NVIDIA Data Loading Library (DALI) primarily used for?

The NVIDIA Data Loading Library (DALI) is primarily designed to optimize data loading and preprocessing for deep learning applications. This library provides an efficient way to handle data pipelines, enabling users to quickly load and preprocess data on the GPU, which helps in reducing the time spent waiting for data to become available for training or inference.

By leveraging DALI, developers can create complex data processing operations that are executed in parallel with model training, thus maximizing resource utilization. This capability is particularly significant when working with large datasets or performing computationally intensive transformations, as it minimizes bottlenecks and facilitates faster training times.

Other options, such as model evaluation, data visualization, and hyperparameter tuning, while important aspects of machine learning workflows, do not align with the core functionality of DALI. The library focuses specifically on the data pipeline aspect, ensuring that data is prepared and available in an optimal format for training deep learning models.